Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

11 papers of 8,653Sort Recent · Most cited
  1. 2020
    Simple Lifelong Learning MachinesJoshua T. Vogelstein, Jayanta Dey, Hayden S. Helm … Carey E. PriebeTPAMI · Johns Hopkins University · Baylor College of Medicine · +1
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  2. 2025
    Enhancing Few-Shot Class-Incremental Learning via Training-Free Bi-Level Modality CalibrationYiyang Chen, Tianyu Ding, Lei Wang … Wenbin LiCVPR · Nanjing University · Microsoft (United States) · +1
  3. 2023
    Cost-effective On-device Continual Learning over Memory Hierarchy with MiroXinyue Ma, Suyeon Jeong, Minjia Zhang … Myeongjae JeonAnnual International Conference on Mobile Computing and N… · Ulsan National Institute of Science and Technology · Microsoft (United States) · +1
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  4. 2022
    Continual Learning about Objects in the Wild: An Interactive ApproachDan Bohus, Sean Andrist, Ashley Feniello … Eric Horvitz2022 International Conference on Multimodal Interaction · Microsoft (United States)
  5. 2021
    Continual Neural Network Model RetrainingXiaofeng Zhu, Diego KlabjanIEEE International Conference on Big Data (Big Data) · Microsoft (United States) · Northwestern University
  6. 2020
    K-Adapter: Infusing Knowledge into Pre-Trained Models with AdaptersRuize Wang, Duyu Tang, Nan Duan … Ming ZhouACL · Fudan University · Microsoft (United States) · +1
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  7. 2019
    AutoML @ NeurIPS 2018 challenge: Design and ResultsHugo Jair Escalante, Wei-Wei Tu, Isabelle Guyon … Qiang YangMachine Learning · Gleason (United States) · National Institute of Astrophysics, Optics and Electronics · +8
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  8. 2018
    An Empirical Study of Example Forgetting during Deep Neural Network LearningMariya Toneva, Alessandro Sordoni, Rémi Tachet des Combes … Geoffrey J. GordonICLR · Carnegie Mellon University · Microsoft (United States) · +1
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  9. 2018
    Accumulating Conversational Skills Using Continual LearningSung‐Jin LeeIEEE Spoken Language Technology Workshop (SLT) · Microsoft (United States)
  10. 2016
    Differentiable Programs with Neural LibrariesAlexander L. Gaunt, Marc Brockschmidt, Nate Kushman, Daniel TarlowICML · Microsoft (United States)
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  11. 2007
    Principles of Lifelong Learning for Predictive User ModelingAshish Kapoor, Eric HorvitzSpringer LNCS · Microsoft (United States)
About this index

We keep this list because we read the field and wanted one place to see it. It covers work on continual learning itself, in the core areas of machine learning, and leaves out papers that apply it inside another field, such as medical imaging or fault diagnosis. It is seeded from the community lists kept by ContinualAI and by Xialei Liu, then filled out from OpenAlex, and every week a script looks for new papers on OpenAlex and arXiv. A model reads each candidate and decides whether it belongs; a person reviews the additions before they go live. Authors and affiliations come from OpenAlex, so a recent preprint can lack its institutions for a week or two.

Missing something, or filed under the wrong venue? Write to hello@unify.ai with the arXiv id or DOI.